Carbonaceous particles have been confirmed as major components of ambient aerosols in urban environments and are related to climate impacts and environmental and health effects. In this study, we collected different-size particulate matter (PM) samples (PM₁, PM_2.5, and PM₁₀) at an urban site in Lanzhou, northwest China, during three discontinuous one-month periods (January, April, and July) of 2019. We measured the concentrations and potential transport pathways of carbonaceous aerosols in PM₁, PM_2.5, and PM₁₀ size fractions. The average concentrations of OC (organic carbon) and EC (elemental carbon) in PM₁, PM_2.5, and PM₁₀ were 6.98 ± 3.71 and 2.11 ± 1.34 μg/m³, 8.6 ± 5.09 and 2.55 ± 1.44 μg/m³, and 11.6 ± 5.72 and 4.01 ± 1.72 μg/m³. The OC and EC concentrations in PM₁, PM_2.5, and PM₁₀ had similar seasonal trends, with higher values in winter due to the favorable meteorology for accumulating pollutants and urban-increased emissions from heating. Precipitation played a key role in scavenge pollutants, resulting in lower OC and EC concentrations in summer. The OC/EC ratios and principal component analysis (PCA) showed that the dominant pollution sources of carbon components in the PMs in Lanzhou were biomass burning, coal combustion, and diesel and gasoline vehicle emissions; and the backward trajectory and concentration weight trajectory (CWT) analysis further suggested that the primary pollution source of EC in Lanzhou was local fossil fuel combustion.

We investigated water-soluble ions (WSIs) of aerosol samples collected from 2016 to 2017 in Lanzhou, a typical semi-arid and chemical-industrialized city in Northwest China. WSIs concentration was higher in the heating period (35.68 ± 19.17 μg/m³) and lower in the non-heating period (12.45 ± 4.21 μg/m³). NO₃⁻, SO₄²⁻, NH₄⁺ and Ca²⁺ were dominant WSIs. The concentration of SO₄²⁻ has decreased in recent years, while the NO₃⁻ level was increasing. WSIs concentration was affected by meteorological factors. The sulfur oxidation and nitrogen oxidation ratios (SOR and NOR) exceeded 0.1, inferring the vital contribution of secondary transformation. Meanwhile higher O₃ concentration and temperature promoted the homogeneous reaction of SO₂. Lower temperature and high relative humidity (RH) were more suitable for heterogeneous reactions of NO₂. Three-phase cluster analysis illustrated that the anthropogenic source ions and natural source ions were dominant WSIs during the heating and non-heating periods, respectively. The backward trajectory analysis and the potential source contribution function model indicated that Lanzhou was strongly influenced by the Hexi Corridor, northeastern Qinghai–Tibetan Plateau, northern Qinghai province, Inner Mongolia Plateau and its surrounding cities. This research will improve our understanding of the air quality and pollutant sources in the industrial environment.

Data on particulate matter, gaseous pollutants, and AQI values from three cities (Haikou, Sanya, and Danzhou) between January 2018 and December 2022 were obtained in order to analyze the spatiotemporal distribution characteristics of air pollution, the correlation between pollutants with meteorological conditions, and the potential sources in Hainan Island. The spatiotemporal distribution’s characteristics demonstrated that the annual mean concentrations of SO₂, NO₂, CO, O₃, PM₁₀ and PM_2.5 were 4.34 ± 1.11 μg m⁻³, 9.87 ± 1.87 μg m⁻³, 0.51 ± 0.06 mg m⁻³, 73.04 ± 6.36 μg m⁻³, 27.31 ± 3.63 μg m⁻³, and 14.01 ± 2.02 μg m⁻³, respectively. The yearly mean concentrations were trending downward in the past few years and were below the National Ambient Air Quality Standard (NAAQS) Grade II. Summer was the season with the lowest concentrations of all pollutants (3.84 μg m⁻³, 7.34 μg m⁻³, 0.42 mg m⁻³, 52.80 μg m⁻³, 18.67 μg m⁻³ and 8.67 μg m⁻³ for SO₂, NO₂, CO, O₃, PM₁₀ and PM_2.5, respectively), and afternoons were the time with the lowest concentrations of pollutants (except for 78.04 μg m⁻³ for O₃). The influence of meteorological conditions on pollutants was examined: there was a prominent positive correlation between temperature and O₃ in summer, and relative humidity largely influenced the concentrations of PM. The pollution in Hainan was affected more by regional transport; according to the backward trajectory results, Hainan is susceptible to air masses from Guangdong and Fujian to the northeast, the Indochina Peninsula to the southwest, and the South China Sea to the southeast. The results of PSCF and CWT analyses indicated that Guangdong, Jiangxi, Hunan, and Fujian were the primary potential sources of PM_2.5 and O₃.

Rapid social development has led to serious air pollution problems in cities, and air pollutants, including gaseous pollutants and particulate matter, have an important impact on climate, the environment, and human health. This study analyzed the characteristics, potential sources, and causes of air pollution in the Wu-Chang-Shi urban cluster. The results showed that NO₂, CO, SO₂, PM₁₀, and PM_2.5 had a tendency to decrease, while O₃ showed an increasing trend. The concentrations of SO₂, NO₂, CO, PM_2.5, and PM₁₀ showed the highest values in winter and the lowest values in summer, with similar seasonal variations. However, the concentration of O₃ was highest in the summer and lowest in the winter. Compared with the pollutant concentrations in other Chinese cities, PM_2.5, PM₁₀, and NO₂ are more polluted in the Wu-Chang-Shi urban. Meteorological factors have a greater impact on pollutant concentrations, with higher concentrations of major pollutants observed when wind speeds are low and specific wind directions are observed, and higher secondary pollutant O₃ concentrations observed when wind speeds are low and specific wind directions are observed. The backward trajectory and concentration weighting analysis show that the particulate pollutants in the Wu-Chang-Shi urban in winter mainly come from Central Asia and surrounding cities. O₃ showed an increasing trend before and after the novel coronavirus outbreak, which may be related to changes in NO_X, volatile organic compounds, and solar radiation intensity, and the concentrations of SO₂, NO₂, CO, PM₁₀, and PM_2.5 showed an overall decreasing trend after the outbreak and was smaller than before the outbreak, which is related to the reduction of industrial and anthropogenic source emissions during the outbreak.